Empirical evidence for impacts of internal migration on vegetation dynamics in China from 1982 to 2000

Migration is one of the major socio-economic characteristics of China since the country adopted the policy of economic reform in late 1970s. Many studies have been dedicated to understand why and how people move, and the consequences of their welfare. The purpose of this study is to investigate the environmental impacts of the large scale movement of population in China. We analyzed the trend in the Normalized Difference Vegetation Index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) along with China migration data from the 1 percent national survey during 1982-1987, the 4th national census during 1985-1990 and the 5th national census during1995~2000. We found that the internal migration in China has a statistically significant negative impact on vegetation growth at the provincial scale from 1982 to 2000 even though the overall vegetation abundance increased in China. The impact from migration (R2=0.47, P=0.0001) on vegetation dynamics is the second strongest as among the factors considered, including changes in annual mean air temperature (R2=0.50, P=0.0001) and annual total precipitation (R2=0.30, P=0.0049) and gross domestic production (R2= 0.25, P=0.0102). The negative statistical relationship between the rate of increase in total migration and the change in vegetation abundance is stronger (R2=0.56, P=0.0000) after controlling for the effects of changes in temperature and precipitation. In-migration dominates the impacts of migration on vegetation dynamics. Therefore, it is important for policy makers in China to take the impacts of migration on vegetation growth into account while making policies aiming at sustainable humanenvironment relations

Permanence and Stability of an Age-Structured Prey-Predator System with Delays

An age-structured prey-predator model with delays is proposed and analyzed. Mathematical analyses of the model equations with regard to boundedness of solutions, permanence, and stability are analyzed. By using the persistence theory for infinite-dimensional systems, the sufficient conditions for the permanence of the system are obtained. By constructing suitable Lyapunov functions and using an iterative technique, sufficient conditions are also obtained for the global asymptotic stability of the positive equilibrium of the model

AKConv: Convolutional Kernel with Arbitrary Sampled Shapes and Arbitrary Number of Parameters

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation be confined to a local window and cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k $\times$ k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. It is obvious that the shape and size of targets are various in different datasets and at different locations. Convolutional kernels with fixed sample shapes and squares do not adapt well to changing targets. In response to the above questions, the Alterable Kernel Convolution (AKConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance. In AKConv, we define initial positions for convolutional kernels of arbitrary size by means of a new coordinate generation algorithm. To adapt to changes for targets, we introduce offsets to adjust the shape of the samples at each position. Moreover, we explore the effect of the neural network by using the AKConv with the same size and different initial sampled shapes. AKConv completes the process of efficient feature extraction by irregular convolutional operations and brings more exploration options for convolutional sampling shapes. Object detection experiments on representative datasets COCO2017, VOC 7+12 and VisDrone-DET2021 fully demonstrate the advantages of AKConv. AKConv can be used as a plug-and-play convolutional operation to replace convolutional operations to improve network performance. The code for the relevant tasks can be found at https://github.com/CV-ZhangXin/AKConv.Comment: 10 pages, 5 figure

Recovery of Outliers in Water Environment Monitoring Data

The water environment monitoring data are time sequences with outliers which depress the data quality, so outlier detection and recovery play an important role in the applications such as knowledge acquisition and prediction modelling of water environment indicators. To detect the outliers, the short-term chain comparison with the sliding window based on the time sequence characteristics is adopted. To recover outliers closer to the real data at that time, the sub-sequences are divided dynamically according to the change characteristics of the dataset, then the similarity between sub-sequences is measured by the shape distance and the outliers are recovered according to the change trend of the corresponding data in the most similar sub-sequences. The monitoring data of a water station are selected in the study. The experimental results show that the recovery method is superior to the commonly used prediction recovery method and fitting recovery method, the recovered data is smoother and the short-term trend is more obvious

Response law and indicator selection of seismic wave velocity for coal seam outburst risk

The accurate detection of coal seam stress field effectively prevents coal and gas outbursts. This study uses wave velocity, wave velocity anomaly coefficient, and wave velocity gradient as indicators to identify stress anomalies in coal seam. The results show that these three indicators of wave velocity are all positively correlated with load, while changes in the wave velocity anomaly coefficient and wave velocity gradient are more gentle than those of wave velocity. The degree of damage of coal can be judged by the wave velocity anomaly coefficient, while the transition between high and low stress zones can be identified by the wave velocity gradient. In areas affected by geological structures such as valleys and mountain tops, the coal seam wave velocity and wave velocity anomaly coefficient may exhibit anomalies. The comparative analysis of wave velocity and its derived indicators can reveal the stress state and coal structure of coal seam with higher accuracy, identify the areas affected by geological structures such as valleys and mountain tops, and determine the boundary of the stress relief zone after hydraulic fracturing. Combined with the actual geological structure characteristics of coal seam, it can accurately identify the stress disturbance region of coal seam and achieve the purpose of predicting coal and gas outbursts.Document Type: Original articleCited as: Qiu, L., Zhu, Y., Liu, Q., Guo, M., Song, D., Wang, A. Response law and indicator selection of seismic wave velocity for coal seam outburst risk. Advances in Geo-Energy Research, 2023, 9(3): 198-210. https://doi.org/10.46690/ager.2023.09.0

Oceanic accretionary belt in the West Qinling Orogen: Links between the Qinling and Qilian orogens, China

We present an integrated study of ophiolite complexes and island arc rocks from the Tianshui-Wushan Accretionary Belt, West Qinling Orogen. The West Qinling Orogen is important because it links the Qinling orogen to the east and the Qilian and Kunlun orogens to the west. The link between these orogens is commonly assumed, but has little study in detail. Zircon U-Pb analyses from ophiolitic rocks indicate the oceanic lithosphere formed in the Cambrian (530–500 Ma). Pillow lavas in the ophiolite complex show geochemical signatures of enriched MORB, suggesting they represent remnants of an oceanic plateau or seamounts. The island arc rocks include a volcanic complex with basalt-andesite and boninite of Late Ordovician age (460–440 Ma), and a serpentinized peridotite massif. The serpentinized peridotite most likely represent a highly refractory mantle residue with subsequent melt-rock interaction at ~450 Ma, suggesting that it formed in a forearc setting. The co-occurrence of ophiolite complexes and island arc rocks indicates that Tianshui-Wushan Accretionary Belt is an oceanic suture zone caused by oceanic subduction in the Early Paleozoic. The island arc rocks most likely represent the early product of an Izu-Bonin-Mariana (IBM)-type intra-oceanic arc, developed in response to a collision between an oceanic plateau and a continental margin. Our study permits a tectonic correlation between the Tianshui-Wushan Accretionary Belt in the West Qinling Orogen and the South Qilian Accretionary Belt in the Qilian Orogen, thereby establishing the continuity between the Early Paleozoic orogenic belts along the southern margin of the North China Craton

Involvement of AmphiREL, a Rel-like gene identified in Brachiastoma belcheri, in LPS-induced response: Implication for evolution of Rel subfamily genes

AbstractRel/NF-κB family genes are important transcriptional factors regulating vital activities of immunity response, but no Rel/NF-κB gene has been identified in amphioxus. In this study, we have not only identified and characterized a Rel-like gene from Brachiastoma belcheri, but also extensively studied the evolution of Rel gene subfamily. We found that: 1) the amphioxus genome contains an AmphiREL gene encoding a Rel/NF-κB homolog, and AmphiREL gene was involved in the innate immune response of LPS stimulation in amphioxus. 2) Gene synteny comparison and structure comparison suggested that AmphiREL is an orthologous gene of human RELB, and is a paralogous gene of human RELA and REL. 3) Structural changes of Rel subfamily proteins are diverse during the evolution process, and imply their functional diversity. 4) The Rel subfamily genes have undergone very strong purifying selection. Together, our results provide important clues for understanding the evolution and function of Rel subfamily genes